Swapped networks: unifying the architectures and algorithms of a wide class of hierarchical parallel processors

In this paper, we propose a new class of interconnection networks, called swapped networks, for general-purpose parallel processing. Swapped networks not only generate a wide class of high-performance interconnection networks, but also generalize, and serve to unify, many proposed parallel architectures as well as their algorithms. We show that swapped networks can efficiently emulate hypercubes, high-dimensional meshes, or generalized hypercubes, while having node degrees significantly smaller than the emulated network in each case. We also show that some subclasses of swapped networks can achieve asymptotically optimal diameters. Swapped networks are highly modularized, make the use of fixed-degree building blocks possible for any practically realizable system, and lead to the construction of high-performance scalable networks with reasonable cost.